GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
RegressionTree Member List

This is the complete list of members for RegressionTree, including all inherited members.

BASE_TYPE_NOT_SET enum value (defined in MLBase)MLBase
baseType (defined in MLBase)MLBaseprotected
BaseTypes enum name (defined in MLBase)MLBase
BEST_ITERATIVE_SPILT enum value (defined in Tree)Tree
BEST_RANDOM_SPLIT enum value (defined in Tree)Tree
buildTree(const RegressionData &trainingData, RegressionTreeNode *parent, Vector< UINT > features, UINT nodeID) (defined in RegressionTree)RegressionTreeprotected
CLASSIFIER enum value (defined in MLBase)MLBase
classType (defined in GRTBase)GRTBaseprotected
classType (defined in GRTBase)GRTBaseprotected
clear()RegressionTreevirtual
CLUSTERER enum value (defined in MLBase)MLBase
computeBestSpilt(const RegressionData &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in RegressionTree)RegressionTreeprotected
computeBestSpiltBestIterativeSpilt(const RegressionData &trainingData, const Vector< UINT > &features, UINT &featureIndex, Float &threshold, Float &minError) (defined in RegressionTree)RegressionTreeprotected
computeNodeRegressionData(const RegressionData &trainingData, VectorFloat &regressionData) (defined in RegressionTree)RegressionTreeprotected
copyBaseVariables(const Regressifier *regressifier)Regressifier
Tree::copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
Regressifier::copyGRTBaseVariables(const GRTBase *GRTBase)GRTBase
copyMLBaseVariables(const MLBase *mlBase)MLBase
createInstanceFromString(const std::string &regressifierType)Regressifierstatic
createNewInstance() const Regressifier
debugLog (defined in GRTBase)GRTBaseprotected
debugLog (defined in GRTBase)GRTBaseprotected
deepCopy() const Regressifier
deepCopyFrom(const Regressifier *regressifier)RegressionTreevirtual
deepCopyTree() const RegressionTreevirtual
enableScaling(const bool useScaling)MLBase
errorLog (defined in GRTBase)GRTBaseprotected
errorLog (defined in GRTBase)GRTBaseprotected
getBaseRegressifier() const Regressifier
getBaseType() const MLBase
Tree::getClassType() const GRTBase
Regressifier::getClassType() const GRTBase
Tree::getGRTBasePointer()GRTBase
Tree::getGRTBasePointer() const GRTBase
Regressifier::getGRTBasePointer()GRTBase
Regressifier::getGRTBasePointer() const GRTBase
Tree::getGRTRevison()GRTBasestatic
Regressifier::getGRTRevison()GRTBasestatic
Tree::getGRTVersion(bool returnRevision=true)GRTBasestatic
Regressifier::getGRTVersion(bool returnRevision=true)GRTBasestatic
getInputRanges() const Regressifier
getInputType() const MLBase
getIsBaseTypeClassifier() const MLBase
getIsBaseTypeClusterer() const MLBase
getIsBaseTypeRegressifier() const MLBase
Tree::getLastErrorMessage() const GRTBase
Regressifier::getLastErrorMessage() const GRTBase
Tree::getLastInfoMessage() const GRTBase
Regressifier::getLastInfoMessage() const GRTBase
Tree::getLastWarningMessage() const GRTBase
Regressifier::getLastWarningMessage() const GRTBase
getLearningRate() const MLBase
getMap() (defined in Regressifier)Regressifierinlineprotectedstatic
getMaxDepth() const Tree
getMaxNumEpochs() const MLBase
getMinChange() const MLBase
getMinNumEpochs() const MLBase
getMinNumSamplesPerNode() const Tree
getMinRMSErrorPerNode() const RegressionTree
getMLBasePointer()MLBase
getMLBasePointer() const MLBase
Tree::getModel(std::ostream &stream) const Treevirtual
Regressifier::getModel(std::ostream &stream) const MLBasevirtual
getModelAsString() const MLBasevirtual
getModelTrained() const MLBase
getNumInputDimensions() const MLBase
getNumInputFeatures() const MLBase
getNumOutputDimensions() const MLBase
getNumSplittingSteps() const Tree
getNumTrainingIterationsToConverge() const MLBase
getOutputRanges() const Regressifier
getOutputType() const MLBase
getPredictedNodeID() const Tree
getRandomiseTrainingOrder() const MLBase
getRegisteredRegressifiers()Regressifierstatic
getRegressifierType() const Regressifier
getRegressionData() const Regressifier
getRemoveFeaturesAtEachSpilt() const Tree
getRootMeanSquaredTrainingError() const MLBase
getScalingEnabled() const MLBase
getTotalSquaredTrainingError() const MLBase
getTrained() const MLBase
getTrainingMode() const Tree
getTrainingResults() const MLBase
getTree() const RegressionTree
getUseValidationSet() const MLBase
getValidationSetAccuracy() const MLBase
getValidationSetPrecision() const MLBase
getValidationSetRecall() const MLBase
getValidationSetSize() const MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::string filename) is deprecated, use save(std::string filename) instead", virtual bool saveModelToFile(std::string filename) const )MLBase
GRT_DEPRECATED_MSG("saveModelToFile(std::fstream &file) is deprecated, use save(std::fstream &file) instead", virtual bool saveModelToFile(std::fstream &file) const )MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::string filename) is deprecated, use load(std::string filename) instead", virtual bool loadModelFromFile(std::string filename))MLBase
GRT_DEPRECATED_MSG("loadModelFromFile(std::fstream &file) is deprecated, use load(std::fstream &file) instead", virtual bool loadModelFromFile(std::fstream &file))MLBase
Tree::GRTBase(void)GRTBase
Regressifier::GRTBase(void)GRTBase
infoLog (defined in GRTBase)GRTBaseprotected
infoLog (defined in GRTBase)GRTBaseprotected
inputType (defined in MLBase)MLBaseprotected
inputVectorRanges (defined in Regressifier)Regressifierprotected
learningRate (defined in MLBase)MLBaseprotected
load(std::fstream &file)RegressionTreevirtual
Regressifier::load(const std::string filename)MLBasevirtual
loadBaseSettingsFromFile(std::fstream &file)Regressifierprotected
map(VectorFloat inputVector)MLBasevirtual
map_(VectorFloat &inputVector)MLBasevirtual
maxDepth (defined in Tree)Treeprotected
maxNumEpochs (defined in MLBase)MLBaseprotected
minChange (defined in MLBase)MLBaseprotected
minNumEpochs (defined in MLBase)MLBaseprotected
minNumSamplesPerNode (defined in Tree)Treeprotected
minRMSErrorPerNodeRegressionTreeprotected
MLBase(void)MLBase
notify(const TrainingResult &data) (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
notify(const TestInstanceResult &data) (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
notifyTestResultsObservers(const TestInstanceResult &data)MLBase
notifyTrainingResultsObservers(const TrainingResult &data)MLBase
NUM_TRAINING_MODES enum value (defined in Tree)Tree
numInputDimensions (defined in MLBase)MLBaseprotected
numOutputDimensions (defined in MLBase)MLBaseprotected
numSplittingSteps (defined in Tree)Treeprotected
numTrainingIterationsToConverge (defined in MLBase)MLBaseprotected
Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inline
Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inline
operator=(const RegressionTree &rhs)RegressionTree
outputType (defined in MLBase)MLBaseprotected
predict(VectorFloat inputVector)MLBasevirtual
predict(MatrixFloat inputMatrix)MLBasevirtual
predict_(VectorFloat &inputVector)RegressionTreevirtual
Regressifier::predict_(MatrixFloat &inputMatrix)MLBasevirtual
print() const RegressionTreevirtual
random (defined in MLBase)MLBaseprotected
randomiseTrainingOrder (defined in MLBase)MLBaseprotected
registerModule (defined in RegressionTree)RegressionTreeprotectedstatic
registerTestResultsObserver(Observer< TestInstanceResult > &observer)MLBase
registerTrainingResultsObserver(Observer< TrainingResult > &observer)MLBase
Regressifier(void)Regressifier
REGRESSIFIER enum value (defined in MLBase)MLBase
regressifierType (defined in Regressifier)Regressifierprotected
regressionData (defined in Regressifier)Regressifierprotected
RegressionTree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const UINT trainingMode=BEST_ITERATIVE_SPILT, const bool useScaling=false, const Float minRMSErrorPerNode=0.01)RegressionTree
RegressionTree(const RegressionTree &rhs)RegressionTree
removeAllTestObservers()MLBase
removeAllTrainingObservers()MLBase
removeFeaturesAtEachSpilt (defined in Tree)Treeprotected
removeTestResultsObserver(const Observer< TestInstanceResult > &observer)MLBase
removeTrainingResultsObserver(const Observer< TrainingResult > &observer)MLBase
reset()Regressifiervirtual
rootMeanSquaredTrainingError (defined in MLBase)MLBaseprotected
save(std::fstream &file) const RegressionTreevirtual
Regressifier::save(const std::string filename) const MLBasevirtual
saveBaseSettingsToFile(std::fstream &file) const Regressifierprotected
scale(const Float &x, const Float &minSource, const Float &maxSource, const Float &minTarget, const Float &maxTarget, const bool constrain=false)MLBaseinline
Tree::setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
Regressifier::setErrorLoggingEnabled(const bool loggingEnabled)GRTBase
Tree::setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
Regressifier::setInfoLoggingEnabled(const bool loggingEnabled)GRTBase
setLearningRate(const Float learningRate)MLBase
setMaxDepth(const UINT maxDepth)Tree
setMaxNumEpochs(const UINT maxNumEpochs)MLBase
setMinChange(const Float minChange)MLBase
setMinNumEpochs(const UINT minNumEpochs)MLBase
setMinNumSamplesPerNode(const UINT minNumSamplesPerNode)Tree
setMinRMSErrorPerNode(const Float minRMSErrorPerNode)RegressionTree
setNumSplittingSteps(const UINT numSplittingSteps)Tree
setRandomiseTrainingOrder(const bool randomiseTrainingOrder)MLBase
setRemoveFeaturesAtEachSpilt(const bool removeFeaturesAtEachSpilt)Tree
setTrainingLoggingEnabled(const bool loggingEnabled)MLBase
setTrainingMode(const UINT trainingMode)Tree
setUseValidationSet(const bool useValidationSet)MLBase
setValidationSetSize(const UINT validationSetSize)MLBase
Tree::setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
Regressifier::setWarningLoggingEnabled(const bool loggingEnabled)GRTBase
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
SQR(const Float &x) const (defined in GRTBase)GRTBaseinlineprotected
StringRegressifierMap typedefRegressifier
targetVectorRanges (defined in Regressifier)Regressifierprotected
testingLog (defined in GRTBase)GRTBaseprotected
testingLog (defined in GRTBase)GRTBaseprotected
testResultsObserverManager (defined in MLBase)MLBaseprotected
totalSquaredTrainingError (defined in MLBase)MLBaseprotected
train(ClassificationData trainingData)MLBasevirtual
train(RegressionData trainingData)MLBasevirtual
train(TimeSeriesClassificationData trainingData)MLBasevirtual
train(ClassificationDataStream trainingData)MLBasevirtual
train(UnlabelledData trainingData)MLBasevirtual
train(MatrixFloat data)MLBasevirtual
train_(RegressionData &trainingData)RegressionTreevirtual
Regressifier::train_(ClassificationData &trainingData)MLBasevirtual
Regressifier::train_(TimeSeriesClassificationData &trainingData)MLBasevirtual
Regressifier::train_(ClassificationDataStream &trainingData)MLBasevirtual
Regressifier::train_(UnlabelledData &trainingData)MLBasevirtual
Regressifier::train_(MatrixFloat &data)MLBasevirtual
trained (defined in MLBase)MLBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
trainingLog (defined in GRTBase)GRTBaseprotected
trainingMode (defined in Tree)Treeprotected
TrainingMode enum name (defined in Tree)Tree
trainingResults (defined in MLBase)MLBaseprotected
trainingResultsObserverManager (defined in MLBase)MLBaseprotected
tree (defined in Tree)Treeprotected
Tree(const UINT numSplittingSteps=100, const UINT minNumSamplesPerNode=5, const UINT maxDepth=10, const bool removeFeaturesAtEachSpilt=false, const UINT trainingMode=BEST_ITERATIVE_SPILT)Tree
useScaling (defined in MLBase)MLBaseprotected
useValidationSet (defined in MLBase)MLBaseprotected
validationSetAccuracy (defined in MLBase)MLBaseprotected
validationSetPrecision (defined in MLBase)MLBaseprotected
validationSetRecall (defined in MLBase)MLBaseprotected
validationSetSize (defined in MLBase)MLBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
warningLog (defined in GRTBase)GRTBaseprotected
~GRTBase(void)GRTBasevirtual
~MLBase(void)MLBasevirtual
~Observer() (defined in Observer< TrainingResult >)Observer< TrainingResult >inlinevirtual
~Observer() (defined in Observer< TestInstanceResult >)Observer< TestInstanceResult >inlinevirtual
~Regressifier(void)Regressifiervirtual
~RegressionTree(void)RegressionTreevirtual
~Tree(void)Treevirtual